From klingai-pack
Provides production checklist for Kling AI video generation integrations, verifying auth, errors, costs, task handling, safety, security, monitoring, and performance before deployment.
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin klingai-packThis skill is limited to using the following tools:
Checklist covering authentication, error handling, cost controls, monitoring, security, and content policy before deploying Kling AI video generation to production.
Creates isolated Git worktrees for feature branches with prioritized directory selection, gitignore safety checks, auto project setup for Node/Python/Rust/Go, and baseline verification.
Executes implementation plans in current session by dispatching fresh subagents per independent task, with two-stage reviews: spec compliance then code quality.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
Checklist covering authentication, error handling, cost controls, monitoring, security, and content policy before deploying Kling AI video generation to production.
.env in repo)Authorization: Bearer <token> format verifiedtask_status: "failed" logs task_status_msgduration sent as string "5" not integer 5standard mode used for non-final renders# Pre-batch credit check
credits_needed = len(prompts) * 10 # 10 credits per 5s standard
if credits_needed > DAILY_BUDGET:
raise RuntimeError(f"Batch needs {credits_needed}, budget is {DAILY_BUDGET}")
callback_url used instead of polling in productionrequests.Session()# Connection pooling
session = requests.Session()
adapter = requests.adapters.HTTPAdapter(pool_connections=5, pool_maxsize=10)
session.mount("https://", adapter)
from kling_client import KlingClient
c = KlingClient()
result = c.text_to_video("test: blue sky with clouds", duration=5, mode="standard")
assert result["videos"][0]["url"], "No video URL"
print("READY FOR PRODUCTION")